For tabular data, the Deepchecks library requires that the model have a predict method for regression tasks and in addition predict_proba method for classification tasks, both of which should be implemented using the scikit-learn API conventions [1]}. Some checks may attempt using additional model methods if those exist. For example, it uses the built-in feature importance property if it exists, and if it does not, it calculates the feature importance using permutation importance procedure [2]}.
Note that built-in scikit-learn classifiers and regressors, along with many additional popular models types (e.g. XGBoost [3]}, LightGBM [4]}, CatBoost[5]} etc.) implement these methods and are thus supported.
